GitHub - thecml/csgo-ai-challenge: Skybox presented an AI challenge that ran from Spring to Fall 2020, where teams had to predict the winner of rounds in the tactical shooter CS:GO. This project uses TensorFlow, Scikit-learn and CatBoost to train robust model ensembles using the most relevant features.

thecml / csgo-ai-challenge Public

Notifications You must be signed in to change notification settings
Fork 0
Star 1

Skybox presented an AI challenge that ran from Spring to Fall 2020, where teams had to predict the winner of rounds in the tactical shooter CS:GO. This project uses TensorFlow, Scikit-learn and CatBoost to train robust model ensembles using the most relevant features.

1 star 0 forks Branches Tags Activity

Name		Name	Last commit message	Last commit date
Latest commit History 42 Commits
models		models
results		results
src		src
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
requirements.txt		requirements.txt
setup.py		setup.py

Repository files navigation

The CS:GO AI Challenge Summer 2020

Dataset: https://www.kaggle.com/christianlillelund/csgo-round-winner-classification

About

Skybox presented an AI challenge that ran from Spring to Fall 2020, where teams had to predict the winner of rounds in the tactical shooter CS:GO. This project uses TensorFlow, Scikit-learn and CatBoost to train robust model ensembles using the most relevant features.

ai gaming tensorflow scikit-learn classification ensemble-learning deeplearning counter-strike-global-offensive esport tensorflow2

Report repository

Releases

No releases published

Packages

No packages published

Languages

Python 100.0%